Research publications, preprints, and any associated presentation materials.
2024
Eliciting In-Context Learning in Vision-Language Models for Videos Through Curated Data Distributional Properties
Keunwoo Peter Yu,
Zheyuan Zhang,
Fengyuan Hu,
Shane Storks,
and Joyce Chai
The 2023 Conference on Empirical Methods in Natural Language Processing
(Miami, FL, USA)
2023
From Heuristic to Analytic: Cognitively Motivated Strategies for Coherent Physical Commonsense Reasoning
Zheyuan Zhang,
Shane Storks,
Fengyuan Hu,
Sungryull Sohn,
Moontae Lee,
Honglak Lee,
and Joyce Chai
The 2023 Conference on Empirical Methods in Natural Language Processing
(Singapore)
Can Foundation Models Watch, Talk, and Guide You Step By Step to Make a Cake?
Yuwei Bao,
Keunwoo Peter Yu,
Yichi Zhang,
Shane Storks,
Itamar Bar-Yossef,
Alex de la Iglesia,
Megan Su,
Xiao Lin Zheng,
and Joyce Chai
Findings of the Association for Computational Linguistics: EMNLP 2023
(Singapore)
NLP Reproducibility For All: Understanding Experiences of Beginners
Shane Storks,
Keunwoo Yu,
Ziqiao Ma,
and Joyce Chai
The 61st Annual Meeting of the Association for Computational Linguistics
(Toronto, ON, Canada)
In-Context Analogical Reasoning with Pre-Trained Language Models
Xiaoyang Hu,
Shane Storks,
Richard L. Lewis,
and Joyce Chai
The 61st Annual Meeting of the Association for Computational Linguistics
(Toronto, ON, Canada)
SEAGULL: An Embodied Agent for Instruction Following Through Situated Dialog
Yichi Zhang,
Jianing Yang,
Keunwoo Yu,
Yinpei Dai,
Shane Storks,
Yuwei Bao,
Jiayi Pan,
Nikhil Devraj,
Ziqiao Ma,
and Joyce Chai
Alexa Prize SimBot Challenge Proceedings
2022
DANLI: Deliberative Agent for Following Natural Language Instructions
Yichi Zhang,
Jianing Yang,
Jiayi Pan,
Shane Storks,
Nikhil Devraj,
Ziqiao Ma,
Keunwoo Peter Yu,
Yuwei Bao,
and Joyce Chai
The 2022 Conference on Empirical Methods in Natural Language Processing
(Abu Dhabi, United Arab Emirates)
Best of Both Worlds: A Hybrid Approach for Multi-Hop Explanation with Declarative Facts
Shane Storks,
Qiaozi Gao,
Aishwarya Reganti,
and Govind Thattai
The First International Workshop on Combining Learning and Reasoning: Programming Languages, Formalisms, and Representations at AAAI-22
(Vancouver, BC, Canada)
2021
Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense Language Understanding
Shane Storks,
Qiaozi Gao,
Yichi Zhang,
and Joyce Chai
Findings of the Association for Computational Linguistics: EMNLP 2021
(Punta Cana, Dominican Republic)
Beyond the Tip of the Iceberg: Assessing Coherence of Text Classifiers
Shane Storks
and Joyce Chai
Findings of the Association for Computational Linguistics: EMNLP 2021
(Punta Cana, Dominican Republic)
Are We There Yet? Learning to Localize in Embodied Instruction Following
Shane Storks,
Qiaozi Gao,
Govind Thattai,
and Gokhan Tur
AAAI-21 Workshop on Hybrid Artificial Intelligence
(Online)
2020
Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches
Shane Storks,
Qiaozi Gao,
and Joyce Y. Chai
arXiv:1904.01172 [cs.CL]
Other talks and guest lectures.
2023
Making Generative AI Better for You: Fine-Tuning & Experimentation for Custom Research Solutions
Invited Talk, November 2023
Michigan Institute for Data Science (MIDAS) Generative AI Tutorial Series
(Ann Arbor, MI, USA)
Tutorial: Fine-Tuning LLMs
Invited Tutorial, November 2023
Michigan Institute for Data Science (MIDAS) Generative AI Tutorial Series
(Ann Arbor, MI, USA)
Commonsense Reasoning in Natural Language Understanding
Guest Lecture, November 2023
EECS 595: Natural Language Processing at University of Michigan
(Ann Arbor, MI, USA)
Cognitive Motivations in Analogical and Physical Reasoning with Large Language Models
Invited Talk, October 2023
University of Michigan Weinberg Institute for Cognitive Science Seminar Series
(Ann Arbor, MI, USA)
Prompt Engineering with Large Language Models: Basics and Research Applications
Invited Talk, July 2023
Generative AI for Research Faculty Workshop at University of Michigan
(Ann Arbor, MI, USA)
2022
Language Model Prompting
Guest Lecture, November 2022
EECS 595: Natural Language Processing at University of Michigan
(Ann Arbor, MI, USA)
Large Pre-Trained Language Models for Physical Action Understanding and Planning
Invited Talk, October 2022
2022 Microsoft Turing Academic Program (MS-TAP) Workshop
(Online)
Learning Physical Action Schemas from Language and Experience
Poster Session, September 2022
DARPA PTG Site Visit at University of Michigan
(Ann Arbor, MI, USA)
Toward Coherent Commonsense Language Understanding in Machines
Guest Lecture, January 2022
EECS 692: Advanced Artificial Intelligence at University of Michigan
(Ann Arbor, MI, USA)
2021
Language Model Prompting
Guest Lecture, December 2021
EECS 595: Natural Language Processing at University of Michigan
(Ann Arbor, MI, USA)
2019
Natural Language Understanding and Inference: Benchmarks, Resources, and Approaches
Invited Talk, October 2019
Stanford University Human-Centered Artificial Intelligence (HAI) and AI Index Workshop on Measurement in AI Policy: Opportunities and Challenges
(Stanford, CA, USA)
2018
Simulating Hot Topic Popularity with a Modified SIR Model
Invited Talk, February 2018
Lawrence Technological University Campus Open House
(Southfield, MI, USA)
2017
Simulating Hot Topic Popularity with a Modified SIR Model
Contributed Talk, July 2017
Mathematical Association of America MathFest
(Chicago, IL, USA)
Courses for which I've served as a Graduate Student Instructor (GSI). Duties typically include assignment and project design, grading, supporting students through office hours and online interactions, and occasionally giving lectures.
EECS 595: Natural Language Processing
Fall 2022
University of Michigan
Graduate introductory NLP course led by Joyce Chai. Topics include syntax, semantics, discourse, deep learning for NLP, and their applications in information extraction, machine translation, and dialogue systems.
Electrical Engineering and Computer Science (EECS)
EECS 595: Natural Language Processing
Fall 2021
University of Michigan
Graduate introductory NLP course led by Joyce Chai. Topics include syntax, semantics, discourse, deep learning for NLP, and their applications in information extraction, machine translation, and dialogue systems.
Electrical Engineering and Computer Science (EECS)
EECS 595: Natural Language Processing
Fall 2020
University of Michigan
Graduate introductory NLP course led by Joyce Chai. Topics include syntax, semantics, discourse, deep learning for NLP, and their applications in information extraction, machine translation, and dialogue systems.
Electrical Engineering and Computer Science (EECS)
Professional appointments in industry.
Amazon Alexa AI
June 2021 - August 2021
Applied Scientist Intern
Natural Understanding, Teachable AI team (remote). Completed a self-contained research project on multi-hop reasoning advised by mentors Qiaozi Gao and Govind Thattai.
Sunnyvale, CA, USA
Amazon Alexa AI
June 2020 - August 2020
Applied Scientist Intern
Natural Understanding, Teachable AI team (remote). Completed a self-contained research project on embodied instruction following advised by mentor Qiaozi Gao.
Sunnyvale, CA, USA
Universal Logistics Holdings, Inc.
January 2017 - July 2018
Junior .NET Developer and Data Analyst
Used C#, VB.NET, and .SQL to create and maintain company databases, warehouse management applications, telemetric data stream processors, and big data visualizations.
Warren, MI, USA
Dominion Technologies Group, Inc.
June 2016 - December 2016
Junior Programmer
Used Visual C# to build and modify user interfaces for automotive assembly machines including fluid fill and alignment.
Roseville, MI, USA
Dominion Technologies Group, Inc.
September 2015 - June 2016
Technical Assistant
Authored and prepared technical manuals for automotive assembly machines. Synthesized schematic diagrams of fluid and electric circuits with input from subject matter experts.
Roseville, MI, USA
Selected awards and other honors I've received.
- Attendee, NextProf Nexus, University of Michigan, Georgia Institute of Technology, & University of California, Berkeley (2024)
- Winner, Alexa Prize SimBot Challenge, Amazon (2023)
- Fall 2022 GSI Award, University of Michigan Computer Science and Engineering Division (2023)
- NLP @ Michigan Best Poster Award, Michigan AI Lab (2022)
- University Distinguished Fellowship, Michigan State University (2018)
- Dean’s Award for Academic Excellence, Lawrence Technological University College of Arts and Sciences (2018)
- Wayne H. and Vita S. Buell Honor Full Scholarship, Lawrence Technological University (2014 - 2018)
Students I've collaborated with and advised on research.
- Itamar Bar-Yossef, University of Michigan
- Megan Su, University of Michigan
- Ruixuan Deng, University of Michigan
- Fengyuan Hu, University of Michigan
- Zheyuan Zhang, University of Michigan
- Nick Hu, Brown University
- Wenfei Tang, NVIDIA
- Haoyi Qiu, University of California, Los Angeles
- Brianna Epstein, ExtraHop
If you're a University of Michigan student interested in my research and would like to work with me, please send me an email.
Unpublished course projects and side projects. Ask me about them if you're interested!
2021
Invariant Extended Kalman Filter for Localization in Underwater Caves
Samuel Ansaldo,
AJ Bull,
Xinyu Ma,
Alyssa Scheske,
and Shane Storks
EECS 568 (Mobile Robotics), University of Michigan
2020
Toward More Faithful Vision-and-Language Navigation Agents
Shane Storks,
Tianrong Zhang,
and Wenyi Wu
EECS 598 (Special Topics: Situated Language Processing for Embodied AI), University of Michigan
2019
Using Twitter to Rank Musical Artist Popularity
Shane Storks
and Andrew Schmidt
CSE 881 (Data Mining), Michigan State University